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BACKGROUND: Shortening is used widely in cookie preparation to improve quality and texture. However, large amounts of saturated and trans fatty acids present in shortening have adverse effects on human health, and much effort has been made to reduce the use of shortening. The use of oleogels might be a suitable alternative. In this study, the oleogels of high oleic sunflower oil with beeswax (BW), BW‐glyceryl monopalmitate (BW‐GMP), and BW‐Span80 (BW‐S80) were prepared and their suitability to replace shortening in cookie preparation was evaluated. RESULTS: The solid fat content of BW, BW‐GMP, and BW‐S80 oleogels was significantly lower than that of commercial shortening when the temperature was not higher than 35 °C. However, the oil‐binding capacity of these oleogels was almost similar to that of shortening. The crystals in the shortening and oleogels were β' form mainly; however, the morphology of crystal aggregates in these oleogels was different from that of shortening. The textural and rheological properties of doughs prepared with the oleogels were similar, and clearly different from those of dough with commercial shortening. The breaking strengths of cookies made with oleogels were lower than that of cookies prepared with shortening. However, cookies containing BW‐GMP and BW‐S80 oleogels were similar in density and color to those prepared with shortening. CONCLUSION: The textural properties and color of cookies with BW‐GMP and BW‐S80 oleogels were very similar to those of the cookies containing commercial shortening. The BW‐GMP and BW‐S80 oleogels could act as alternatives to shortening in the preparation of cookies. © 2023 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Genetic diversity is the determinant of the allocation of germplasm resources in the genetic improvement of aquaculture species. In this study, three F1 families, including a hybrid Scylla family (S. paramamosain ♂ × S. serrata ♀), a paternal family of S. paramamosain, a maternal family of S. serrata, and two wild populations, including a paternal population of S. paramamosain and a maternal population of S. serrata, were used to investigate the genetic diversity and genetic difference. The results indicated that 98 alleles of nine microsatellites loci were observed in five Scylla populations. The highest average value of Ho (observed heterozygosity), He (expected heterozygosity), and PIC (polymorphic information content) of the wild S. paramamosain population were 0.790, 0.799, and 0.771, respectively, suggesting the wild paternal population has high genetic diversity. The comparative analysis of PIC, Fst (fixation index), and HWE (Hardy–Weinberg equilibrium) indicated that the paternal S. paramamosain may be more suitable for artificial breeding than the maternal S. serrata from the perspective of allele frequency. Analysis of molecular variance analysis (AMOVA) showed that the total genetic variation mainly occurred within populations (73.28%), demonstrating that artificial breeding may induce genetic differentiation of the family groups of Scylla. The results of the analysis of Fst value, UPGMA (unweighted pair-group mean analysis) dendrogram, and genetic diversity indicated that the F1 hybrid offspring had a close genetic distance and high genetic identity with the paternal S. paramamosain populations. It indicated that the F1 hybrid offspring showed potential paternal genetic affinities and a similar potential for artificial breeding with S. paramamosain. The study will provide valuable information to evaluate the difference in the genetic diversity and population structure between hybrid offspring and distinct parental populations of Scylla. [ABSTRACT FROM AUTHOR]

Multimodal multiobjective optimization problem (MMOP) is a special kind of multiobjective optimization problem (MOP) with multimodal characteristics, where multiple different Pareto optimal sets (PSs) map to the same Pareto optimal front (PF). To handle MMOPs, a decomposition-based harmony search algorithm (called MOEA/D-HSA) is devised. In MOEA/D-HSA, multiple individuals who are assigned to the same weight vector form a subpopulation for finding multiple different PSs. Then, an environmental selection method based on greedy selection is designed to dynamically adjust the subpopulation scale for keeping the population diversity. Finally, the modified harmony search algorithm and elite learning strategy are utilized to balance the diversity and convergence of the population. Experimental results on the CEC 2019 test suite reveal that MOEA/D-HSA has superior performance than a few state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]

Multiobjective Multitasking Optimization (MO-MTO) has become a hot research spot in the field of evolutionary computing. The fundamental problem of MO-MTO is to inhibit the negative transfer phenomenon. Mining the relationship among multiple optimization tasks and identifying the effective transferred knowledge have been proven a feasible way for the inhibition of negative transfer. In this paper, the solutions of different tasks are regarded as the vertices of two separate sets. Through constructing the bipartite graph of the vertices from these two sets, the relationship of different populations can be expressed and the valuable knowledge can be identified to transfer. Furthermore, a historical knowledge correction strategy is designed to deal with some special cases when identifying knowledge by the bipartite graph. A series of experiments are conducted on two MO-MTO test suits, and the results have demonstrated the efficacy of the proposed algorithm. [ABSTRACT FROM AUTHOR]

• Precipitation events trigger the pulse N 2 O emissions. • All sizes of precipitation events significantly increase cumulative N 2 O emissions. • Cumulative N 2 O emission after precipitation events parabolically varied with precipitation event sizes. • N addition amplifies the response of cumulative N 2 O emissions to precipitation events. • Precipitation event size plus long-term N addition led to substantial differences in N 2 O emissions. Precipitation events and nitrogen (N) addition play important roles in regulating nitrous oxide (N 2 O) emissions in semi-arid grassland ecosystems. The effects of precipitation events, long-term N addition, and their interaction on N 2 O emissions, however, remain largely unclear. We conducted a mesocosm experiment to examine how long-term N addition (0 and 10 g N m−2 yr−1, from 2011 to 2020) affects N 2 O emission responses to a gradient of manipulated precipitation events (0, 5, 10, 20, and 50 mm). The precipitation events had pulsing effects on N 2 O emissions due to the stimulation of microbial activity and substrate availability. Precipitation events significantly parabolically increased cumulative N 2 O emissions. Long-term N addition substantially enhanced cumulative N 2 O emissions response to precipitation events. The precipitation events and long-term N addition synergistically improved cumulative N 2 O emissions. The water-filled pore space and ammonium nitrogen content were the most important factors driving the temporal dynamics and accumulation of N 2 O emissions following the precipitation events and long-term N addition. Our study indicates that N addition affects the N 2 O emissions responses to precipitation events, which are essential for understanding the response of N 2 O emissions to global change. [ABSTRACT FROM AUTHOR]

The ordinary differential equation is a powerful tool for analyzing optimization algorithm. Motivated by the fact, this paper revisits Halpern fixed-point algorithm from an ordinary differential equation. More specifically, we establish a second-order ordinary differential equation with Hessian-driven damping, which is the limit of Halpern fixed-point algorithm. The Hessian-driven damping makes it possible to significantly attenuate the oscillations. [ABSTRACT FROM AUTHOR]

A two-phase evolutionary algorithm is developed to find multiple solutions of a nonlinear equations system. It transforms a nonlinear equations system into a multimodal optimization problem. In phase one of the proposed algorithm, a strategy combines a multiobjective optimization technique and a niching technique to maintain the population diversity. Phase two consists of a detection method and a local search method for encouraging the convergence. The detection method finds several promising subregions and the local search method locates the corresponding optimal solutions in each promising subregion. The experiments on a set of 30 nonlinear equation systems demonstrate that the proposed algorithm is better than other state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]

We validated the daily formation of increments in otoliths of yellow goosefish Lophius litulon using reared individuals to examine the growth in the field. Single, round-shaped core structures were observed in 41% of sagittae and in 73% of the lapilli. Therefore, lapillar otoliths were used for further observations of daily increment analysis. The lapillus radius of newly hatched larvae was 15.0 ± 1.4 μm (mean ± standard deviation) forming the hatch check (first check). At 6 days after hatching (DAH), the second check was observed, which may correspond to the energy transition from endogenous to exogenous nutrition, located at 28.1 ± 0.7 μm from the core structures. Thereafter, clear daily increments formed outside the check. To estimate larval growth in the field, we examined the relationship between the notochord length (NL) and lapillus radius by an allometric equation. The mean growth rate was estimated as ca. 0.18 mm in NL/day during 10–40 DAH. The results of this study provide insights into the previously unknown early life history and will enable further understanding of the population dynamics of the genus Lophius. [ABSTRACT FROM AUTHOR]

Abstract Permafrost ecosystems play an important role in global climate change, and climate warming would result in permafrost thawing and changing microbial mediated N cycles. Emissions of nitrous oxide (N 2 O) are an important component of N budgets in high-latitude permafrost ecosystems, especially in the context of global climate change. However, few studies have investigated the emissions of N 2 O from a swamp forest in a permafrost ecosystem. In this paper, we investigated the N 2 O emissions rates and cumulative budget from continuous permafrost region in the Daxing'an Mountains, northeast China, and identified the key environmental factors affecting N 2 O emissions from three swamp forests in the growing season. A bootstrapping model estimated that average N 2 O fluxes during the growing season were 40.76 ± 6.13, 29.56 ± 3.21 and 38.27 ± 8.46 μg m−2 h−1 from three swamp forests consisting of Larix gmelinii - Ledum palustre var. dilatatum (LL), Larix gmelinii - Carex appendiculata (LC) and Betula fruticose - Carex schmidtii (BC), respectively. The types of swamp forests had no statistically significant impact on N 2 O emissions (P > 0.05). The cumulative N 2 O emissions were estimated to be 1.07 ± 0.09 (LL), 0.79 ± 0.18 (LC) and 1.05 ± 0.11 kg ha−1 (BC) in the swamp forests, indicating that the permafrost region of the Daxing'an Mountains might be a potential N 2 O source during the growing season. The N 2 O emissions were mainly controlled by soil temperature, water table level, pH, ammonium nitrogen, nitrate nitrogen, total organic carbon and the carbon-to-nitrogen ratio. N 2 O emission showed significant negative correlation with nitrate nitrogen in the three swamp forests; thus, the low nitrate would limit the rate of N 2 O emissions in the permafrost region. In addition, we found that denitrification could be the potential source of N 2 O fluxes in the permafrost region of Daxing'an Mountains. Our results indicated that permafrost swamp forests were significant source for N 2 O emissions, and N 2 O emissions were controlled by multiple environmental factors. Graphical abstract Image 1 Highlights • N 2 O emissions from permafrost in the Daxing'an Mountains, China were estimated. • The types of permafrost swamp forest did not significant effect N 2 O emissions. • N 2 O emissions from permafrost region were controlled by multiple environmental factors. • Denitrification is a potential source of N 2 O fluxes in permafrost region of the Daxing'an Mountains. [ABSTRACT FROM AUTHOR]

Aims: The aim of this study was to quantify and understand the driving factors of the spatial variation of soil respiration ( R) in an old-growth mixed broadleaved-Korean pine forest in northeastern China. Methods: All woody stems ≥1 cm diameter at breast height (DBH) were measured in the 9 ha plot. Simultaneous measurements of R, soil temperature ( T) and soil water content ( W) were conducted for 256 sampling points on a regular 20-m grid refined with 512 additional sampling points randomly placed within each of the 20-m blocks in May, July and September of 2014. Results: The variogram analyses revealed 87-91 % of the sample variance was explained by autocorrelation over a range of 15 to 23 m during the observation periods. The R were highly correlated among the measurements made in May, July and September. The model indicated that the W, bulk density (BD) and maximum DBH for trees within 3 m (radius) of the measurement collars explained 46 % of the spatial variation in R seasonally averaged across three observations. Conclusions: The spatial patterns of R remained constant across the three measurement campaigns. The spatial variation in R was primarily controlled by the W and forest stand structure. [ABSTRACT FROM AUTHOR]

Objective: To assess the responses to taper in endurance athletes using meta-analysis. Methods: Systematic searches were conducted in China National Knowledge Infrastructure, PubMed, Web of Science, SPORTDiscus, and EMBASE databases. Standardized mean difference (SMD) and 95% confidence interval (CI) of outcome measures were calculated as effect sizes. Results: 14 studies were included in this meta-analysis. Significant improvements were found between pre- and post-tapering in time–trial (TT) performance (SMD = −0.45; P < 0.05) and time to exhaustion (TTE) performance (SMD = 1.28; P < 0.05). However, There were no improvements in maximal oxygen consumption (V˙O2max) and economy of movement (EM) (P > 0.05) between pre- and post-tapering. Further subgroup analysis showed that tapering combined with pre-taper overload training had a more significant effect on TT performance than conventional tapering (P < 0.05). A tapering strategy that reduced training volume by 41–60%, maintained training intensity and frequency, lasted ≤7 days, 8–14 days, or 15–21 days, used a progressive or step taper could significantly improve TT performance (P < 0.05). Conclusions: The tapering applied in conjunction with pre-taper overload training seems to be more conducive to maximize performance gains. Current evidence suggests that a ≤21-day taper, in which training volume is progressively reduced by 41–60% without changing training intensity or frequency, is an effective tapering strategy. [ABSTRACT FROM AUTHOR]

To evaluate the effects of forest transition (conversion of primary temperate forest into secondary forest and plantations) on rhizospheric ( R R ) and heterotrophic respiration ( R H ), we used the trenching-plot and infrared gas exchange analyzer approaches to partition soil respiration ( R S ) for four temperate forest types in northeast China, including the primary mixed broadleaved-Korean pine ( Pinus koraiensis ) forest, secondary birch ( Betula platyphylla ) forest, Dahurian larch ( Larix gmelinii ) plantation and Korean pine plantation, throughout the growing season (May–October) in 2011 and 2012. The results showed that R S and its components displayed obvious seasonal dynamics and were mainly controlled by soil temperature. Furthermore, incorporating soil moisture into the pure R S ( R H )-temperature model improved the prediction of R S and R H in most forest types ( R S , R 2 = 0.687–0.799; R H , R 2 = 0.721–0.849). The apparent temperature sensitivity ( Q 10 ) of R R (2.69–5.16) was higher than that of R H (2.34–2.56) in all forest types. The average R H was increased by 35% following the conversion of primary forest to secondary birch forest, 31% to larch plantation and 19% to pine plantation. Such increment of R H could be explained by the increase of soil organic carbon storage in the top soil. When the primary forest was converted to secondary birch forest, the average R R significantly increased ( P < 0.05), but no significant differences in R R between primary forest and two plantations were detected ( P > 0.05). The differences in R R between secondary birch forest and primary forest and two plantations may reflect differences in small root biomass (<5 mm in diameter) at a depth of 0–40 cm and with soil microbial biomass carbon in the top soil. Our results suggest that mechanisms controlling R H and R R are probably different and that partitioning soil respiration when evaluating the effect of forest conversion on soil respiration is important. [ABSTRACT FROM AUTHOR]

• MTB induced the increase of Polyketides and Glycerophospholipids in macrophages. • MB induced the level of Glycerophospholipids and Sterol Lipids of macrophages. • MTB promotes the formation of foam cells of macrophage for its colonization. Mycobacterium tuberculosis (M. tuberculosis (MTB) and M. bovis (MB) of the Mycobacterium tuberculosis complex (MTBC) are the causative agents of the notorious infectious disease tuberculosis (TB) in a range of mammals, including bovine and human. The lipid composition of MTB/MB performed imperative function as invading host macrophage. However, the detailed variations in lipid compositions of MTB and MB were unknown, while the responses relevant to lipid metabolisms in MTB /MB-infected host were also unclear. In the present study, a dual-Lipidomics were used to elucidate the differences in lipid composition of MTB and MB and responses in lipid metabolisms of primary bovine alveolar macrophages infected by MTB/MB. The Lipidomics showed significant differences in lipid composition, especially differences in levels of Glycerophospholipids, Sterol Lipids, Fatty Acyls and Polyketides between these two mycobacterium species. Meanwhile, both MTB and MB could invoke various responses of lipid metabolisms in host macrophages. An infection of MTB mainly induced the increases of Polyketides and Glycerophospholipids in macrophages, whereas an MB infection induced the increases of Glycerophospholipids and Sterol. Furthermore, TAG 13:0–18:5–18:5 of MTB and PC (16:1(9E)/0:0), PI(20:2(11Z,14Z)/22:6(4Z,7Z,10Z,13Z,16Z,19Z)), 4, 6-Decadiyn-1-ol isovalerate and LacCer (d18:1/24:1(15Z)) of MB were identified to cause variations in lipid metabolisms of macrophages, respectively. From these data, we proposed that the differential compositions of lipid compositions in MTB and MB could successfully colonize in macrophage by different mechanisms. MTB could promote the formation of foam cells of macrophage for its colonization and development, while MB mainly suppresses the macrophage autophagy to escape the immune responses of host. [ABSTRACT FROM AUTHOR]

Abstract: The artificial bee colony (ABC) algorithm is a relatively new optimization technique which has been shown to be competitive to other population-based algorithms. However, there is still an insufficiency in the ABC algorithm regarding its solution search equation, which is good at exploration but poor at exploitation. Inspired by differential evolution (DE), we propose a modified ABC algorithm (denoted as ABC/best), which is based on that each bee searches only around the best solution of the previous iteration in order to improve the exploitation. In addition, to enhance the global convergence, when producing the initial population and scout bees, both chaotic systems and opposition-based learning method are employed. Experiments are conducted on a set of 26 benchmark functions. The results demonstrate good performance of ABC/best in solving complex numerical optimization problems when compared with two ABC based algorithms. [Copyright &y& Elsevier]

It is a challenging task to optimize network structure and connection parameters simultaneously in a single hidden layer feedforward neural network (SLFN). Extreme learning machine (ELM) is a popular non-iterative learning method in recent years, which often provides good generalization performance of a SLFN at extremely fast learning speed, yet only for fixed network structure. In this work, a cooperative binary-real genetic algorithm (CGA) based on ELM, called CGA-ELM, is proposed to adjust the structure and parameters of a SLFN simultaneously for achieving a compact network with good generalization performance. In CGA-ELM, a hybrid coding scheme is designed to evolve the network structure and input parameters, i.e., input weights between input nodes and hidden nodes as well as the biases of hidden nodes. Then output parameters, i.e., output weights between hidden nodes and output nodes, are determined by the ELM. A combination of training error and network complexity is taken as the fitness function to evaluate the performance of a SLFN. A binary GA is responsible for optimizing network structure, while a real GA and the ELM optimize collaboratively network parameters. Experimental results on classification applications demonstrate that CGA-ELM outperforms CGA and ELM significantly in terms of the generalization ability. Also, CGA-ELM has more competitive capacity when compared with other state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]

In artificial neural network (ANN) learning, empirical risk can be expressed by training error, while structural risk can be expressed by network complexity. Learning from data is often seen as a tradeoff between these two risks. Additionally, balancing training error and validation error can overcome the overfitting problem to some extent. It is known that the network performance is also related to regularization term. In order to consider four factors, i.e. training error, validation error, network complexity and regularization term simultaneously in the training process of a single-hidden layer feedforword neural network (SLFN), a many-objective coevolutionary learning algorithm (MOCELA) integrated with extreme learning machine auto-encoder (ELMAE), called MOCELA-ELMAE is presented. In MOCELA, the non-dominated sorting genetic algorithm III (NSGA-III) is improved for handling the many-objective optimization model with hybrid variables, where binary coding is used for structure learning and real coding is utilized for representing input parameters, referring to all input weights and hidden biases of the AE network. Output parameters of AE, i.e. output weights are analytically calculated by the non-iterative learning rule. The network structure and connection parameters of SLFN are determined based on those of AE. A set of Pareto optimal solutions are eventually collected by the MOCELA-ELMAE, which represents multiple optimal SLFNs. To make the final decision, three best SLFNs with minimum validation errors are selected as the base classifiers for selective ensemble learning. Extensive experiments are implemented on the benchmark classification data sets of UCI machine learning repository, and obvious improvements have been observed when the proposed MOCELA-ELMAE is compared with the NSGA-III based on hybrid coding and completely non-iterative learning of SLFN respectively. The experimental results also illustrate that the MOCELA-ELMAE performs much better than other state-of-the-art learning algorithms on many data sets. • Many-objective optimization training model is constructed for a SLFN. • The NSGA-III with new genetic operators is utilized to handle the hybrid variables. • The improved NSGA-III is proposed to optimize structure and input parameters of AE. • A selective neural network ensemble learning is used to improve the output result. [ABSTRACT FROM AUTHOR]

In the context of global climate warming, spring thaw period had been changed in the permafrost regions, which significantly affect heat and water dynamics, along with soil microbial community structure and diversity, and microbially-mediated nitrogen cycle changes. However, in - situ N 2 O emission research is scarce in the permafrost regions and the drivers of N 2 O emission during spring thaw period remain unclear. We selected three type of swamp forests in the permafrost region to investigate the N 2 O emissions during spring thaw period from 17 March to 23 May 2017. We found that N 2 O emission ranged from −35.75 to 74.17 μg m−2 h−1 in the permafrost region during spring thaw period, and there was no significant large burst of N 2 O emissions as observed in other ecosystems. The N 2 O emission during spring thaw period were lower than those from growing season, which were significant affected by soil temperature. During spring thaw period, swamp forest types had no significantly influence on N 2 O emissions, which mainly limited by NO 3 −-N content. Stepwise multiple linear regression indicated that the air temperature, thawing depth, soil temperature, soil moisture, pH, NH 4 +-N, NO 3 −-N, TOC, TN, and C/N ratio were the environmental factors which significant effecting the N 2 O emissions. In the field campaign, cumulative N 2 O emissions were mainly controlled by thawing depth, soil moisture, pH, NH 4 +-N, NO 3 −-N and TN during spring thaw period. Overall, the results demonstrate that in the permafrost ecosystems spring thaw period is an important source of N 2 O emissions. Image 1 • The N 2 O emission during spring thaw period were lower than those from growing season. • There was no significant large burst of N 2 O emission from the permafrost region. • The forest types did not significant influence on N 2 O flux during spring thaw period. • The N 2 O emission from the permafrost region were lower than most ecosystems. [ABSTRACT FROM AUTHOR]

To assess the skiing economy (SE) and kinematics during double poling (DP) roller skiing between two groups of skiers in a field setting. Five experienced and five novice male skiers performed a SEDP test at 16 km∙h−1 on an outdoor athletics track. Gas exchange parameters were measured to determine SEDP. A two-dimensional video was filmed to measure the kinematics variables. Experienced skiers exhibited a 21% lower oxygen cost than novice skiers (p = 0.016) in DP, indicating a strong association between SEDP, cycle length and cycle rate (p < 0.001). Additionally, before the poling phase, experienced skiers manifested significantly greater maximum hip and knee extension angles than novice skiers (p < 0.001). During the poling phase, experienced skiers with a greater pole plant angle (p = 0.001), longer flexion time (p < 0.001) and higher flexion angular velocity in the elbow joint (p < 0.05) demonstrated better SEDP. There was an interaction effect of the one-repetition maximum bench press × group in SEDP (b = − 0.656, SE = 0.097, t = − 6.78, p = 0.001). Therefore, experienced skiers with better SEDP demonstrated more efficient cycles, potentially accomplished using dynamic full-body DP motion to ascertain effective propulsion. Combined upper body strength and ski-specific skill training may enhance SEDP in novice skiers. [ABSTRACT FROM AUTHOR]

Purpose: Colorectal cancer (CRC) screening has been implemented in Tianjin, China since 2012. The objective was to estimate the neoplasia detection rate in a high-risk population by age and sex and to investigate the potential factors associated with colorectal neoplasia. Patients and methods: This study is based on data of the Tianjin CRC screening program from 2012 to 2020. Residents with a positive high-risk factors questionnaire (HRFQ) or a positive faecal immunochemical test (FIT) were identified as high-risk participants and were subsequently recommended for a free colonoscopy. Results: A total of 4,117,897 eligible participants aged 40–74 years completed both a HRFQ and FIT, and 217,164 (5.3%) of them were identified as high-risk participants. Positive rates of preliminary screening increased with age and were higher in females than in males. For 57,971 participants undertaking colonoscopy, the detection rates of nonadvanced adenoma, advanced adenoma and CRC were 37.8%, 5.7% and 1.6%, respectively. Detection rates of advanced neoplasia increased from the age of 50 and were higher in males. For nonadvanced neoplasia, a strong increase was observed in males from the age of 40 and in females from the age of 50. Male sex had a greater impact on individuals aged 40–49 than on older individuals. Several factors including current smoking, drinking, and higher body mass index (BMI) were significantly associated with the presence of neoplasia, whereas, these associations were mainly restricted to individuals aged above 50 but not those aged 40–49 years. Conclusions: These findings support that age-specific risk stratification and sex-specific initiating ages for CRC screening should be recommended to improve the accuracy and effectiveness of current screening strategy. [ABSTRACT FROM AUTHOR]

Grasslands across arid and semi‐arid regions are predicted to experience reductions in precipitation frequency. Besides, grassland degradation has become a serious problem in many of these areas. Despite increasing evidence suggesting compound effects of these synchronous alterations on biotic and abiotic ecosystem constituents, we still do not know how they will impact the coupling among ecosystem constituents and its consequences on ecosystem functioning.Here, we assessed the effects of decreased precipitation frequency and grassland degradation on ecosystem coupling, quantified based on the mean strength of pairwise correlations among multispecies communities and their physicochemical environment, individual functions and ecosystem multifunctionality, and reported their relationships within a mechanistic plant–nematode–micro‐organism–soil interactions framework.Decreased precipitation frequency led to poorly coupled ecosystems, and reduced aboveground plant biomass, soil water content, soil nutrient levels, soil biota abundance and multifunctionality. By contrast, belowground plant biomass and soil potential enzyme activities increased under decreased precipitation frequency treatment. Severe degradation resulted in decoupled ecosystems and suppressed most of individual functions and multifunctionality. Using structural equation modelling, we showed that coupling had a strong direct positive effect on multifunctionality (standardized total effect: 0.74), while multifunctionality was weakened by greater soil water variation (−0.54) and higher soil pH (−0.53).The great sensitivity of ecosystem coupling to altered precipitation regimes and degradation highlights the importance of considering interactions among biotic and abiotic components when predicting early ecological impacts under changing environments. Moreover, the positive relationship between ecosystem coupling and functioning suggests that restoration of degraded grasslands may be achieved by intensifying ecological interactions. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Weight elimination offers a simple and efficient improvement of training algorithm of feedforward neural networks. It is a general regularization technique in terms of the flexible scaling parameters. Actually, the weight elimination technique also contains the weight decay regularization for a large scaling parameter. Many applications of this technique and its improvements have been reported. However, there is little research concentrated on its convergence behavior. In this paper, we theoretically analyze the weight elimination for cyclic learning method and determine the conditions for the uniform boundedness of weight sequence, and weak and strong convergence. Based on the assumed network parameters, the optimal choice for the scaling parameter can also be determined. Moreover, two illustrative simulations have been done to support the theoretical explorations as well. [ABSTRACT FROM AUTHOR]

Identification of ubiquitination sites is central to many biological experiments. Ubiquitination is a kind of post-translational protein modification (PTM). It is a key mechanism for increasing protein diversity and plays a vital role in regulating cell function. In recent years, many models have been developed to predict ubiquitination sites in humans, mice and yeast. However, few studies have predicted ubiquitination sites in Arabidopsis thaliana. In view of this, a deep network model named PrUb-EL is proposed to predict ubiquitination sites in Arabidopsis thaliana. Firstly, six features based on the protein sequence are extracted with amino acid index database (AAindex), dipeptide deviates from the expected mean (DDE), dipeptide composition (DPC), blocks substitution matrix (BLOSUM62), enhanced amino acid composition (EAAC) and binary encoding. Secondly, the synthetic minority over-sampling technique (SMOTE) is utilized to process the imbalanced data set. Then a new classifier named DG is presented, which includes Dense block, Residual block and Gated recurrent unit (GRU) block. Finally, each of six feature extraction methods is integrated into the DG model, and the ensemble learning strategy is used to gain the final prediction result. Experimental results show that PrUb-EL has good predictive ability with the accuracy (ACC) and area under the ROC curve (auROC) values of 91.00% and 97.70% using 5-fold cross-validation, respectively. Note that the values of ACC and auROC are 88.58% and 96.09% in the independent test, respectively. Compared with previous studies, our model has significantly improved performance thus it is an excellent method for identifying ubiquitination sites in Arabidopsis thaliana. The datasets and code used for the article are available at https://github.com/Tom-Wangy/PreUb-EL.git. [Display omitted] • A new model is proposed to predict ubiquitination sites with high accuracy. • AAindex, DDE, DPC, BLOSUM62, EAAC and Binary are applied to extract features from the datasets. • The SMOTE oversampling method is utilized to process the imbalanced data set. • A new classifier named DG is presented, which includes Dese block, Residual block and GRU block. • Six feature extraction methods are adpoted for base classifiers, and ensemble learning strategy is used for final result. [ABSTRACT FROM AUTHOR]

Retinoid X receptor alpha (RXRA) is a well-characterized factor that regulates lipid metabolism; however, the regulatory mechanism in muscle cells of poultry is still unknown. The overexpression and the knockdown of RXRA in myoblasts (CS2 cells), RT-PCR, and western blotting were used to detect the expression levels of genes and proteins related to PPAR-signaling pathways. Intracellular triglycerides (TGs), cholesterol (CHOL), and nonesterified free fatty acids (NEFAs) were detected by the Elisa kit. Fat droplets were stained with Oil Red O. The double-fluorescein reporter gene and chromatin immunoprecipitation (CHIP) were used to verify the relationship between RXRA and candidate target genes. The RXRA gene was highly expressed in duck breast muscle, and its mRNA and its protein were reduced during the differentiation of CS2 cells. The CS2 cells, with the overexpression of RXRA, showed reduced content in TGs, CHOL, NEFAs, and lipid droplets and upregulated the mRNA expression of CD36, ACSL1, and PPARG genes and the protein expression of CD36 and PPARG. The knockdown of RXRA expression in CS2 cells enhanced the content of TGs, CHOL, NEFAs, and lipid droplets and downregulated the mRNA and protein expression of CD36, ACLS1, ELOVL6, and PPARG. The overexpression of the RXRA gene, the activity of the double-luciferase reporter gene of the wild-type CD36 promoter was higher than that of the mutant type. RXRA bound to −860/−852 nt, −688/−680 nt, and −165/−157 nt at the promoter region of CD36. Moreover, the overexpression of CD36 in CS2 cells could suppress the content of TGs, CHOL, NEFAs, and lipid droplets, while the knockdown expression of CD36 increased the content of TGs, CHOL, NEFAs, and lipid droplets. In this study, the transcription factor, RXRA, inhibited the accumulation of TGs, CHOL, NEFAs, and fat droplets in CS2 cells by promoting CD36 expression. [ABSTRACT FROM AUTHOR]

Background: Given the limited effectiveness of the current Chinese colorectal cancer (CRC) screening procedure, adherence to colonoscopy remains low. We aim to develop and validate a scoring system based on individuals who were identified as having a high risk in initial CRC screening to achieve more efficient risk stratification and improve adherence to colonoscopy.Methods: A total of 29,504 screening participants with positive High-Risk Factor Questionnaire (HRFQ) or faecal immunochemical test (FIT) who underwent colonoscopy in Tianjin from 2012-2020 were enrolled in this study. Binary regression analysis was used to evaluate the association between risk factors and advanced colorectal neoplasia. Internal validation was also used to assess the performance of the scoring system.Results: Male sex, older age (age ≥ 50 years), high body mass index (BMI ≥ 28 kg/m2), current or past smoking and weekly alcohol intake were identified as risk factors for advanced colorectal neoplasm. The odds ratios (ORs) for significant variables were applied to construct the risk score ranging from 0-11: LR, low risk (score 0-3); MR, moderate risk (score 4-6); and HR, high risk (score 7-11). Compared with subjects with LR, those with MR and HR had ORs of 2.47 (95% confidence interval, 2.09-2.93) and 4.59 (95% confidence interval, 3.86-5.44), respectively. The scoring model showed an outstanding discriminatory capacity with a c-statistic of 0.64 (95% confidence interval, 0.63-0.65).Conclusions: Our results showed that the established scoring system could identify very high-risk populations with colorectal neoplasia. Combining this risk score with current Chinese screening methods may improve the effectiveness of CRC screening and adherence to colonoscopy. [ABSTRACT FROM AUTHOR]

Background:  Screening recommendations for colorectal cancer (CRC) are mainly based on family history rather than lifestyle risk factors. We aimed to assess and compare risk factors for colorectal neoplasm (CRN) and evaluate trends in neoplasm detection rates during the three rounds of screening from 2012 to 2020 in Tianjin, China.Methods: This study was based on 89,535 first-recorded colonoscopies in Tianjin CRC screening program, 2012-2020. Of these, 45,380 individuals with complete family history and lifestyle factors were included for population attributable fraction (PAF) estimation.Results:  The overall detection rate of nonadvanced adenomas, advanced adenomas and CRC was 39.3%, 5.9% and 1.5%, respectively. The PAFs of current smoking, alcohol consumption, physical activity, higher BMI and family history of CRC, respectively, were 8.9%, 2.6%, 1.9%, 5.8%, and 1.1% for males with nonadvanced CRN; 12.3%, 7.3%, 4.9%, 7.2%, and 0.8% for males with advanced CRN; 3.4%, 0.4%, 2.1%, 7.8%, and 0.7% for females with nonadvanced CRN; and 4.3%, 0.2%, 8.2%, 8.5%, and -0.6% for females with advanced CRN. The PAFs of selected lifestyle factors were 19.9% for males with nonadvanced CRN, 29.0% for males with advanced CRN, 9.7% for females with nonadvanced CRN and 13.8% for females with advanced CRN.Conclusions:  Modifiable lifestyle factors, including smoking, alcohol consumption, physical activity and BMI, have a larger contribution to CRN than family history of CRC. Our findings will provide references for developing guidelines of CRC prevention and control in China. [ABSTRACT FROM AUTHOR]

This paper proposes a hybrid model based on decomposition for constrained optimization problems. Firstly, a constrained optimization problem is transformed into a biobjective optimization problem. Then, the biobjective optimization problem is divided into a set of subproblems, and different subproblems are assigned to different Fitness functions by the direction vectors. Different from decomposition-based multiobjective optimization algorithms in which each subproblem is optimized by using the information of its neighboring subproblems, the neighbors of each subproblem are deFined based on corresponding direction vector only in the method. By combining three main components, namely, the local search model, the global search model, and the direction vector adjusting strategy, the population can gradually move toward the global optimal solution. Experiments on two sets of test problems and Five real-world engineering design problems have shown that the proposed method performs better than or is competitive with other compared methods. [ABSTRACT FROM AUTHOR]

Vibrio mimicus is a pathogenic bacterium that cause red body disease in Macrobrachium nipponense , leading to high mortality and financial loss. Based on previous studies, rpoS gene contribute to bacterial pathogenicity during infection, but the role of RpoS involved in the immune response of M. nipponense under V. mimicus infection remains unclear. In this study, the pathogen load and the RNA-seq of M. nipponense under wild-type and Δ rpoS strain V. mimicus infection were investigated. Over the entire infection period, the Δ rpoS strain pathogen load was always lower than that of the wild-type strain in the M. nipponense hemolymph, hepatopancreas, gill and muscle. Furthermore, the expression level of rpoS gene in the hepatopancreas was the highest at 24 hours post infection (hpi), then the samples of hepatopancreas tissue infected with the wild type and Δ rpoS strain at 24 hpi were selected for RNA-seq sequencing. The results revealed a significant change in the transcriptomes of the hepatopancreases infected with Δ rpoS strain. In contrast to the wild-type infected group, the Δ rpoS strain infected group exhibited differentially expressed genes (DEGs) enriched in 181 KEGG pathways at 24 hpi. Among these pathways, 8 immune system-related pathways were enriched, including ECM-receptor interaction, PI3K-Akt signaling pathway, Rap1 signaling pathway, Gap junction, and Focal adhesion, etc. Among these pathways, up-regulated genes related to Kazal-type serine protease inhibitors, S-antigen protein, copper zinc superoxide dismutase, tight junction protein, etc. were enriched. This study elucidates that rpoS can affect tissue bacterial load and immune-related pathways, thereby impacting the survival rate of M. nipponense under V. mimicus infection. These findings validate the potential of rpoS as a promising target for the development of a live attenuated vaccine against V. mimicus. • The mutant of rpoS gene can reduce the pathogen load in M. nipponense tissues.. • RpoS is crucial in M. nipponense immune response to V. mimicus.. • Targeting rpoS gene can enhance M. nipponense survival against V. mimicus infection.. [ABSTRACT FROM AUTHOR]

Broadband near-infrared (NIR) light-emitting diodes (LED) with excellent efficiency, and thermal stability are vital light sources for NIR spectroscopic techniques. Nevertheless, there are currently some drawbacks to oxide NIR phosphors, including poor thermal stability. This work has successfully synthesized a series of double perovskite A 2 InTaO 6 (A = Ca, Sr, Ba) phosphors by a conventional high-temperature solid-state method. Using component regulation, the NIR emission peaks span from 866 to 928 nm with a full-width at half maximum (FWHM) of 192 nm. The photoluminescence quantum yield (PLQY) is improved by 23.5%. Moreover, upon 495 nm excitation, the fluorescence intensity of Ba 2 InTaO 6 : Cr3+ at 373 K maintains 72.4% of the initial value at 298 K. Eventually, the ideal phosphor has been fabricated into an NIR-emitting LED and demonstrated its benefits in the night vision application. • The NIR-emitting A 2 InTaO 6 :Cr3+ (A = Ca, Sr, Ba) phosphors were synthesized by component regulation. • A 2 InTaO 6 :Cr3+, with an FWHM greater than 186 nm, achieve ultra-broadband NIR emissions ranging from NIR-I to NIR-II window. • The thermal stability of A 2 InTaO 6 :Cr3+ increases from 48.3% to 72.4%. • A 2 InTaO 6 :Cr3+ phosphors have promising night vision applications and give an approach for fabricating a tunable NIR emitter. [ABSTRACT FROM AUTHOR]

Soil Freeze-Thaw Cycles (FTCs) can provide large amounts of labile C and N to microorganisms to stimulate nitrous oxide (N 2 O) production and emission in the soil. To explore the effects of FTCs on N 2 O fluxes in the pristine riparian marsh, we used the static chamber-GC techniques to investigate N 2 O fluxes in the marsh meadow Calamagrostis angustifolia wetland (MMCW), Ecotone wetland (EW) and Carex Schmidtii Meinsh. marsh (CSMM) in Sanjiang Plain from March to April 2016. The results showed that the three marshes were potential sources of N 2 O during FTC S. The variations of N 2 O fluxes in the three marshes were significantly different (P < 0.001) during FTC S. Principal component analysis and regression analysis indicated that soil NH 4 +-N and NO 3 −-N content were the main driving factors of N 2 O fluxes in MMCW. Though significant correlations were observed between N 2 O fluxes and soil NH 4 +-N content in 0 to10 cm soil depth in EW (r = 0.98, P < 0.01) and in CSMM (r = 0.93, P < 0.05) respectively, the driving factors of N 2 O fluxes during FTC S in EW and CSMM were uncertain. In conclusion, soil FTC S might contribute to the emissions of N 2 O in the pristine riparian marshes. [ABSTRACT FROM AUTHOR]

Cu-Sn alloy was put in the high-temperature hot compression test with a strain rate of 0.01 s−1 and distortion temperature of 550-700 °C. Electron backscattered diffraction technology was adopted to analyze the distortion and microstructure features of different parts of the alloy. The results indicate that: As the temperature rises, the distribution frequency of the Σ3n (n = 1, 2, 3) grain boundary increases to 41.9% from 6.8% but drops suddenly at 650 °C, which is similar to the frequency distribution changes in recrystallization and twin crystals. Meanwhile, multiple annealing twin crystals are generated and connected to form grain clusters with Σ3n orientation among each other. In the inverse pole figure, with the recrystallization continuing, the polar densities of the fiber textures of varied orientations in T1, T2, T3, T4 and other areas decreased gradually; in tensile test of Cu-Sn Alloy, yield strength and tensile strength at break decrease slowly. [ABSTRACT FROM AUTHOR]

Nitrogen (N) addition typically increases nitrous oxide (N 2 O) emissions, but the magnitude of this effect depends on land use type and intensity. Grazing has an important influence on grassland N dynamics, but it is not clear to what extent grazing may interact with N addition in affecting grassland N 2 O emissions. We investigated the mechanisms underlying the individual and interactive effects of N addition and cattle grazing (control (CK), N addition (N), grazing (G), and N addition plus grazing (N + G) treatments) on N 2 O emissions in a temperate meadow steppe by measuring N 2 O fluxes, weather factors, vegetation parameters and soil properties from October 2017 to September 2018. The studied temperate meadow steppe was a source of N 2 O emissions during the experimental period. Approximately 80 % of the annual N 2 O emissions were released during the plant growing season. The highest N 2 O emission was detected in the N + G plots, which indicated the grazing treatment amplified the stimulating effects of N addition on N 2 O emissions. The results from structural equation model (SEM) suggested that N addition enhanced N 2 O emission through increases in NH 4 +-N concentration and soil potential net nitrification rate (N nitri); grazing promoted N 2 O emissions by increasing substrate availability directly via excreta or indirectly through trampling-associated soil aggregate disruption and substrate release. N 2 O emissions increased most strongly with N addition and grazing due to the synergetic effects between animal trampling, animal excreta and available N on the processes of nitrification and denitrification. Overall, our results suggest that the interactive effects of grassland management and global change factors on N 2 O emissions need to be considered for the accurate assessment of grassland greenhouse gas emissions. • The studied temperate meadow steppe was a source of N 2 O emissions. • N addition and grazing did not change the seasonal distribution pattern of N 2 O emissions. • Grazing promoted N 2 O emissions through trampling and excretion. • Grazing amplified the stimulating effect of N addition on N 2 O emissions. • N 2 O fluxes were correlated with soil bulk density, inorganic N content and pH. [ABSTRACT FROM AUTHOR]

• AR is more sensitive to nitrogen addition and grazing than HR. • N addition and grazing had additive effects on AR. • Aboveground biomass is the predominant controlling factor and key predictor of AR. • N addition, grazing and their interaction had no significant effects on HR. • Grazing dampened the positive response of Q 10 of HR to N addition. A quantitative understanding of temporal patterns of soil respiration (SR) and its components, as well as of their controlling factors, are key to the estimation of grassland C sequestration under different scenarios of land-use change and global change. However, the sensitivity of seasonal patterns and magnitude of SR and its components to N addition (N) and grazing (G) and their interactions remains poorly understood. We carried out an experiment with N, G and N addition plus grazing (NG) treatments in temperate meadow steppe located in the easternmost of the Eurasian steppe. We measured SR and its components, i.e., autotrophic respiration (AR) and heterotrophic respiration (HR), along with a suite of other biotic and abiotic factors over 3 years. N addition increased AR when compared to the control treatment (CK), whereas moderate grazing decreased AR, and N addition and grazing had additive effects on AR. We found that aboveground biomass was the predominant controlling factor of AR. However, the N, G and NG treatments had no significant effects on HR. Although N addition and grazing caused changes in a series of biotic and abiotic factors (e.g. total PLFAs, soil fungal/bacterial ratio and bulk density) that controlled soil microbial metabolic processes, collectively these effects on HR appeared to offset each other. Moreover, compared to the CK and N treatments, G and NG treatments reduced the apparent temperature sensitivity (Q 10) of AR and HR. Grazing dampened the positive response of Q 10 of HR to N addition. Our study suggests that AR and HR are regulated by different underlying mechanisms and respond differently to N and G, and therefore should be modeled separately to improve models and predictions of ecosystem C cycling. Our study also indicates that moderate grazing could produce beneficial effects on meadow steppe carbon sequestration under future scenarios of nitrogen deposition and climate warming. [ABSTRACT FROM AUTHOR]